Yiğit, Fatih2023-07-032023-07-032023Yiğit, F. (2023). A three-stage fuzzy neutrosophic decision support system for human resources decisions in organizations. Decision Analytics Journal, 100259.2772-6622https://hdl.handle.net/20.500.12939/3553This study proposes an integrated Decision Support System (DSS) with Multi-Criteria Decision-Making (MCDM) to evaluate trainers in organizations and choose the most suitable one(s) for a training program. The clustering stage determines the most appropriate number of trainees to be assigned to a trainer. The proposed model also considers the training budget and the constraint limiting the number of assignments. The proposed model has three stages: Delphi, the Interval-Valued Neutrosophic Analytic Hierarchy Process (IVN-AHP), and Fuzzy C-Means (FCM). The model’s input is expert opinions on various criteria, the candidate assessment score, and the bi-comparison of agreed criteria. Outputs are weights, and the members of each cluster represent possible candidates. We present a case study to demonstrate the applicability of the proposed DSS in a training program assessment. Additional applications of the proposed system include recruitment and promotioneninfo:eu-repo/semantics/openAccessAnalytic hierarchy processDecision support systemFuzzy c-means algorithmHuman resources analyticsMulti-criteria decision-makingNeutrosophic setsArticle72-s2.0-85161723949Q1